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Volume 3, Issue 6, Pages 372-382 (November 2009)


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Automated 3-dimensional quantification of noncalcified and calcified coronary plaque from coronary CT angiography

Damini Dey, PhDabCorresponding Author Informationemail address, Victor Y. Cheng, MDa, Piotr J. Slomka, PhD, FCCPM, FACCab, Ryo Nakazato, MDa, Amit Ramesh, MSca, Swaminatha Gurudevan, MDa, Guido Germano, PhD, FACCab, Daniel S. Berman, MD, FACCab

Received 17 April 2009; accepted 16 September 2009. published online 05 October 2009.

Introduction

We aimed to develop an automated algorithm (APQ) for accurate volumetric quantification of non-calcified (NCP) and calcified plaque (CP) from Coronary CT angiography (CCTA).

Methods

APQ determines scan-specific attenuation thresholds for lumen, NCP, CP and epicardial fat, and applies knowledge-based segmentation and modeling of coronary arteries, to define NCP and CP components in 3D. We tested APQ in 29 plaques for 24 consecutive scans, acquired with dual-source CT scanner. APQ results were compared to volumes obtained by manual slice-by-slice NCP/CP definition and by interactive adjustment of plaque thresholds (ITA) by 2 independent experts.

Results

APQ analysis time was <2 sec per lesion. There was strong correlation between the 2 readers for manual quantification (r = 0.99, p < 0.0001 for NCP; r = 0.85, p < 0.0001 for CP). The mean HU determined by APQ was 419 ± 78 for luminal contrast at mid-lesion, 227 ± 40 for NCP upper threshold, and 511 ± 80 for the CP lower threshold. APQ showed a significantly lower absolute difference (26.7 mm3 vs. 42.1 mm3, p = 0.01), lower bias than ITA (32.6 mm3 vs 64.4 mm3, p = 0.01) for NCP. There was strong correlation between APQ and readers (R = 0.94, p < 0.0001 for NCP volumes; R = 0.88, p < 0.0001, for CP volumes; R = 0.90, p < 0.0001 for NCP and CP composition).

Conclusions

We developed a fast automated algorithm for quantification of NCP and CP from CCTA, which is in close agreement with expert manual quantification.

a Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building, A238, Los Angeles, CA 90048, USA

b Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

Corresponding Author InformationCorresponding author.

 Conflict of interest: The authors report no conflicts of interest.

 This study was supported by American Heart Association Grant-in-Aid Award 09GRNT2330000, by a grant from the Lincy Foundation, and in part by grant 6318 from the Glazer Foundation, Los Angeles, CA.

PII: S1934-5925(09)00505-X

doi:10.1016/j.jcct.2009.09.004


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